Amount Of Greenhouse Gas Emissions Research Articles

Climate neutrality through economic growth, digitalisation, eco-innovation and renewable energy in European countries

PurposeThe purpose of this paper is to analyse the influence of economic growth, digitalisation, eco-innovation, energy consumption and patents on environmental technologies on the volume of greenhouse gas emissions (GHG) recorded in European countries for a period of nine years (2010–2018).Design/methodology/approachTwo empirical methods were integrated into the theoretical approach developed based on the analysis of the current scientific framework. Multiple linear regression, an extended version of the OLS model, and a non-causal analysis as a robustness method, Dumitrescu–Hurlin, were used to achieve the proposed research objective.FindingsDigitalisation described by the number of individual Internet users and patents on environmental technologies determines the amount of GHG in Europe, and economic growth continues to have a significant effect on the amount of emissions, as well as the consumption of renewable energy. European countries are not framed in well-established patterns, but the economic growth, digitalisation, eco-innovation and renewable energy have an impact on the amount of GHG in one way or another. In many European countries, the amount of GHGs is decreasing as a result of economic growth, changes in the energy field and digitalisation. The positive influence of economic growth on climate neutrality depends on its degree of sustainability, while patents have the same conditional effect of their translation into environmentally efficient technologies.Research limitations/implicationsThis study has a number of limitations which derive, first of all, from the lack of digitalisation indicators. The missing data restricted the inclusion in the analysis of variables relevant to the description of the European digitalisation process, also obtaining conclusive results on the effects of digitalisation on GHG emissions.Originality/valueA similar analysis of the relationship among the amount of greenhouse gas emissions and economic growth, digitalisation, eco-innovation and renewable energy is less common in the literature. Also, the results can be inspirational in the sphere of macroeconomic policy.

Climate Change and Urban Transport Sustainability

The 2022 Sea Level Rise Technical Document, published by the US National Oceanic and Atmospheric Administration (NOAA), reports sea level along the US coastline is projected to rise, on average, 10 - 12 inches (0.25 - 0.30 meters) in the next 30 years (2020-2050) (NOAA, 2022). This will create coastal flooding by causing tide and storm surge heights to increase and reach further inland. By 2050, “moderate” (typically damaging) flooding is expected to occur, on average, more than 10 times as often as it does today, and can be intensified by local factors. About 2 feet (0.6 meters) of sea level rise along the US coastline is increasingly likely between 2020 and 2100 because of emissions to date. Failing to curb future emissions could cause an additional 1.5 - 5 feet (0.5 - 1.5 meters) of rise for a total of 3.5 - 7 feet (1.1 - 2.1 meters) by the end of this century. At the same time, cities are experiencing rapid urbanization and population growth with increasing levels of private motorized vehicle ownership and use, a major source of emissions. Non-motorized transport is considered one of the important mitigation strategies to reduce the amount of greenhouse gas emissions and make urbanized communities sustainable. This paper examines the impacts of sea level rise on non-motorized transportation facilities along the coastlines of the State of Delaware using Geographic Information System (GIS) supported by the latest data and models. Results show there is significant damage in the number of facilities if sea level rises between 2 and 6 feet. As sea level rise projection gets higher, the number of facilities with major inundation increases. So the question becomes with trails and bikeways disappearing along the coastlines, is there enough space to bring these sites to the cities that are further inland, noting that vehicle use is at an all-time high, and, there are grass roots movements everywhere asking decision-makers, engineers and planners for more non-motorized transport facilities? This paper also examines the challenging policy, engineering and planning implications of creating non-motorized transport sites and capacities in cities with shrinking available land and space for such facilities.

BoatNet: automated small boat composition detection using deep learning on satellite imagery.

Tracking and measuring national carbon footprints is key to achieving the ambitious goals set by the Paris Agreement on carbon emissions. According to statistics, more than 10% of global transportation carbon emissions result from shipping. However, accurate tracking of the emissions of the small boat segment is not well established. Past research looked into the role played by small boat fleets in terms of greenhouse gases, but this has relied either on high-level technological and operational assumptions or the installation of global navigation satellite system sensors to understand how this vessel class behaves. This research is undertaken mainly in relation to fishing and recreational boats. With the advent of open-access satellite imagery and its ever-increasing resolution, it can support innovative methodologies that could eventually lead to the quantification of greenhouse gas emissions. Our work used deep learning algorithms to detect small boats in three cities in the Gulf of California in Mexico. The work produced a methodology named BoatNet that can detect, measure and classify small boats with leisure boats and fishing boats even under low-resolution and blurry satellite images, achieving an accuracy of 93.9% with a precision of 74.0%. Future work should focus on attributing a boat activity to fuel consumption and operational profile to estimate small boat greenhouse gas emissions in any given region.

Sustainability, emission trading system and carbon leakage: An approach based on neural networks and multicriteria analysis

Two transitions, green and digital, are changing the operations and strategies of industrial systems. At the same time, businesses are challenged to be globally competitive. Europe has a very ambitious agenda as it aims to be the first climate-neutral continent in 2050. The european emissions trading scheme (EU ETS) has proven to have facilitated the reduction of significant amounts of greenhouse gas emissions, but the risk of carbon leakage is present. This work seeks to explore these issues and their relationships. Through the use of a long short-term memory (LSTM) neural network, a model is built to determine the price of european union allowance (EUA) as a function of different financial energy futures. The results show that the model is very robust and the EUA tends to vary between 78 and 91 €/tCO2. In addition, a multi-criteria decision analysis (MCDA) is applied to identify the best policy alternatives to enable businesses subject to the EU ETS to be competitive in global markets. The analysis is carried out with the help of academic and industrial experts and it emerges that the criteria considered most relevant are two: (i) public expenditure and its expected benefits and (ii) the industrial ecosystem. The policy implications identify that bonuses should be provided to businesses for innovative solutions that protect both the energy and raw material components. The framework of the 3E (Energy Efficiency, Renewable Energy, and Circular Economy) are critical to businesses' long-term strategies, flanked by digital development.

Survey Paper About Carbon Footprint

The aim of this proof of concept is to develop a framework to trace the carbon footprints emitted by fossil fuels during power generation. The framework will utilize a life cycle assessment approach to identify the amount of greenhouse gas emissions associated with each stage of the power generation process, from raw material (fuel) extraction to power delivery. The proof of concept will focus on the use of coal and natural gas, which are the most widely used fossil fuels in power generation.The data collected from sources is used to create model which can help us to estimate the amount of carbon footprint generated from different types of power plants like coal-fired power plants and natural gas-fired power plants.The results of this proof of concept are analyzed to identify areas where we can reduce the greenhouse gas emission and also to develop and deploy strategies to transition to cleaner sustainable energy sources.Overall, this concept will provide a valuable tool for energy policymakers and stakeholders to make informed decisions about reducing carbon footprints from fossil fuel power generation

Proposed innovation reform model for the mineral nitrogen fertilizer industry in China to reduce greenhouse gas emissions

<List> <ListItem> <ItemContent> ● The carbon footprint of the nitrogen fertilizer chain has decreased significantly over the last decade. </ItemContent> </ListItem> <ListItem> <ItemContent> ● Different nitrogen fertilizer products have different carbon footprints. </ItemContent> </ListItem> <ListItem> <ItemContent> ● Structural improvement of N fertilizer products can achieve carbon reduction. </ItemContent> </ListItem> </List> Globally, the reduction of excessive N losses and greenhouse gas (GHG) emissions is a central environmental challenge in the 21 century. China has huge associated emissions during both production and land application phases. In addition, 70% of N fertilizer in China is produced and land applied as urea, which has high associated emissions. This study utilized life cycle analysis to compare the carbon emission capacity of different N fertilizers and quantified GHG emissions from different N fertilizer chains within China. This enabled a new innovative reform model to be proposed, which aims to decrease the carbon footprint and increase the net ecosystem carbon budget of China. The results showed that the carbon footprint of the N fertilizer industry was about 229 Tg·yr⁻¹ CO₂-eq in 2020. Through changes away from urea through the production and land application of a mix of newly emerging fertilizers, liquid fertilizers and standard fertilizer reductions to 174–182 Tg·yr⁻¹ CO₂-eq. Through the upgrading of mineral N fertilizer production technology, the carbon footprint of N fertilizer chain can be reduced by 34.8 Tg·yr⁻¹ CO_2-eq. Such reductions would reduce China’s total GHG emissions to 140–147 Tg·yr⁻¹ CO₂-eq.

Assessment of Spatial and Temporal Modeling on Greenhouse Gas Emissions From Electricity Generation

This paper highlights the importance of precise assessments of greenhouse gas (GHG) emissions associated with power generation for effective policy making in environmental sustainability. The current assessment approaches based on historical data or estimated generation using energy models may not accurately reflect the reality of future power systems due to the impact of spatial-temporal and techno-economic characteristics of generation mix and load demands. To address this, the paper presents a comprehensive methodology for accurately quantifying the geographical and temporal variations in GHG emissions associated with generating units’ operation, startup, and shutdown at an hourly resolution. The methodology is based on a detailed electricity model that considers various sources of generation, techno-economic, and spatial-temporal characteristics of system components. The study demonstrates the effectiveness of the methodology in quantifying GHG emissions in the IEEE RTS-GLMC system, with a focus on CO2, N2O, and CH4. The analysis reveals significant variations in GHG emissions among different generation buses and hours of the year, attributed to the high proportion of renewable energy in the generation mix. The paper emphasizes the inadequacy of examining marginal environmental impacts based on GHG emission intensity alone and suggests a more thorough analysis based on total GHG emissions generation. Finally, the paper emphasizes the crucial role of time-varying and marginal assessment techniques in identifying effective strategies for reducing GHG emissions in the electricity sector, including optimizing the operation and capacity of generation units, energy storage systems, and electric vehicles, including their locations.

ANALISIS KEKUATAN FRAME SEPEDA LISTRIK NGEBUTS MENGGUNAKAN METODE ELEMEN HINGGA

Three hundred and ten million people are affected by global climate change caused by carbon dioxide gas. The internal combustion engine that dominates the transportation fleet is one of the contributors to the amount of carbon dioxide in the atmosphere. Research related to environmentally friendly vehicles, in this case, electric vehicles, needs to continue to be carried out followed by downstream research results in the industry. The hope is to reduce the amount of greenhouse gas emissions produced by internal combustion engine vehicles. This study aims to determine the strength of the electric bicycle frame by conducting a stress analysis using the finite element method. The geometry modeling, inputs (data of material properties, geometry, loads, boundary conditions), mesh, solve, and validation are the steps that are passed in this research. The results show that the maximum equivalent stress (von Mises) of 98.31 MPa occurs at the joint between the Seat Tube and Seat Stay, while the minimum stress of 0.01 MPa occurs at the top of the Head Tube. The maximum deformation that occurs at the top of the Seat Tube is 0.15 mm. The minimum safety factor value on the frame is 2.39. Based on this value, the electric bicycle frame can be said to be strong enough to withstand the load of the rider and the battery.

Estimation of Carbon and Biomass Trees Outside Forest (Tof) Using Remote Sensing and GIS Case Study in Vikarabad District, Telangana State India

Abstract: Geospatial technology, remote sensing (RS), geographic information system (GIS), and global positioning system (GPS), commonly called the three 'S' systems, and field inventory methods with hyper spectral sensors play a major role in developing effective forest information. Management to realize scientific management of system forest resources ,Non-forest trees play an important role in global carbon cycling, as they are large pools of carbon as well as potential carbon sinks and atmospheric sources. Given the importance of biomass estimates in the global carbon (C) cycle, the present study demonstrates the potential of stand wise trees outside of forest inventory data, and we specifically used Cartosat-1 panchromatic (2.5 m) and multispectral. LISS-IV (5.8 m) dataset to quantify vegetation and create a much-needed database for TOF. The total geographical study area of Vikarabad district is 104903 sq.km. Results will help address key ecosystem services in the TOF, including quantifying greenhouse gas emissions from agriculture, forests and other land use categories. What is different from the above TOF biomass is that the TOF biomass averaged 2150.12 t/ha in all three classes linear, polygonal and scattered. Total TOF biomass and carbon content above ground were calculated as 24.43 t/ha, 414.46 t/ha and 556.36 t/ha respectively in the study area. The results of the study conclude that classification of TOF and prediction of biomass and carbon content in TOF can be successful. Achieved through a combined approach of remote sensing and GIS based spatial techniques with supplement of field data. The current approach would help to find potential carbon sequestration area in Vikarabad District Telangana State India

Energy balance and greenhouse gas (GHG) emissions of Sauceboat Pepper (Capsicum annuum L.) production in Türkiye

In this study, the efficiency of energy consumption and the amount of greenhouse gas emissions from the cultivation of sauceboat pepper were determined. The experiments and research data are based on the 2020 growing season and were conducted in the Karaisali district of Adana province, Turkey. The primary data used in this study, such as the financial system, labor efficiency, fuel consumption levels, weights of tools and machinery used in sauceboat pepper production, fertilizer, and seedling quantities, were obtained from existing calculations, previous studies, and various sources. The energy ratio, specific energy, energy productivity, and net energy in sauceboat pepper were calculated as 0.82, 0.98 MJ kg-1, 1.02 kg MJ-1, and -6845.51 MJ ha-1, respectively. In the case of the sauceboat peppers, the energy of the fuel oil had the highest share of the total energy input, 31.65%. It was followed by energy for planting seedlings, energy for fertilizer, water energy for irrigation, energy for human labour, energy for spraying, and energy for machinery, with 21.55%, 19.64%, 12.55%, 8.59%, 4.45%, and 1.87%, respectively. Total GHG emissions were estimated as 3703.54 kgCO2-eq ha-1 for sauceboat pepper highest-quality production portion in human labour (31.18%). Human labour was followed by diesel fuel consumption (25.79%), machine (0.08%), seedling planting (15.90%), nitrogen fertilizer (15.88%), phosphate fertilizer (4.09%), herbicides (3.68%), fungicides (1.93%), calcium consumption (0.09%), magnesium application (0.08%) and iron (0.52%). In addition, the GHG value for the production of sauceboat peppers was calculated to be 0.096 kgCO2-eq kg-1.

Assessing U.S. consumers' carbon footprints reveals outsized impact of the top 1%

Unsustainable environmental degradation and extreme economic inequality are two of humanity's most pressing challenges. They are intimately linked. Climate-altering greenhouse gas (GHG) emissions are disproportionately driven by consumption among wealthy and socially privileged groups, yet poorer and socially marginalized peoples face disproportionate climate harms. Here we use the Eora MRIO database and Consumer Expenditure Surveys to quantify GHG emissions related to goods and services consumed by United States households between 1996 and 2019 - including construction of a synthetic dataset to estimate top 1% and top 0.1% household emissions. Top 1% households are of particular interest because their emissions have been largely missed or simplistically and inaccurately estimated in past analysis, yet they exert disproportionate political power in shaping U.S. climate policy. Results suggest significant GHG inequality across economic class and racial lines. In 2019, we estimate the U.S. top 0.1% had emissions (955 t CO2e) 57× higher than bottom decile U.S. households and 597× higher than an average low-income country household. White non-Hispanic household emissions were 1.3× higher than Black households. If climate policy does not account for such extreme emissions disparities, it will limit effectiveness, erode public support, and disproportionately harm economic and socially marginalized groups.

A Transition towards a Food and Agricultural System That Includes Both Food Security and Planetary Health.

This theoretical paper builds on a multidisciplinary framework which is structured to acknowledge the need to combine different research disciplines to understand the problems within our current unsustainable food system and be able to develop possible solutions through new innovations. Current food production methods come at an environmental cost as they generate large amounts of greenhouse gas emissions which affect biodiversity and climate change. The article shows that the problems surrounding food systems and our culture around food, are multifaceted and intricate. The fact is that a growing number of citizens suffer from obesity with various consequential diseases as a result, while a part of the population is still malnourished and dying of hunger. This paper summarizes results from some fairly new studies and different international policy reports to try to clarify how broad the problem is, which is crucial to find new pathways forward to address the problems. Through theoretical discussion, the paper identifies some of the deep underlying root causes and fundamental reasons as to why the urgent needed change is so slow.

Global warming impact and energy analysis of tofu product: A case study in ABC factory Merauke

Tofu is one of the staple foods that are in demand by the wider community due to its high nutritional content, especially protein, and has quite a lot of processed variants. Therefore, the production of tofu must be developed to obtain the best quality, and adequate quantity of production and at the same time, become a product with an environmentally friendly production process. There are still many conventional tofu factories found in Merauke. However, its production process is still a little concerned about environmental aspects. This study aims to identify inputs, outputs, and environmental impacts of the tofu product life cycle, determine potential sources of impact (hotspots) and recommend improvement scenarios. The Life Cycle Assessment (LCA) method is used to estimate and analyze the potential environmental impacts that occur due to the production of 1 kilogram of tofu products at ABC Factory in Merauke. The environmental impact produced by this tofu product is the potential for global warming, so the amount of greenhouse gas emissions that occur will be analyzed. In addition, energy efficiency will be calculated, and conclusions and interpretations will be drawn from the previously analyzed inventory results. The limitation of the system used in this study starts from the soybean cultivation process, transportation of raw materials, and the process of making tofu at ABC Factory. From the results obtained that tofu with local soybean generates GHG emissions is 0.337 kg CO2-eq per kg of tofu, while tofu with imported soybean is 0.801 kg CO2-eq per kg of product. Energy efficiency is indicated by the Net Energy Value (NEV) and the Net Energy Ratio (NER) of the tofu products. The Tofu with local soybean has NEV is 3.529 MJ, while tofu with imported soybean is 0.961 MJ. The value of NER>1 for both tofu products. From the results of inventory analysis, several alternatives can be recommended to reduce the environmental impact that occurs.

Are all ultra‐processed foods created equal?

Are all ultra‐processed foods created equal?

Decomposition of microplastics: Emission of harmful substances and greenhouse gases in the environment

Few reports have been reported on the conditions of the decomposition of plastics in the environment and their threats, while the influence of the decomposition of plastics as a potential factor in increasing greenhouse gas emissions has not been investigated. Greenhouse gases from the decomposition of plastics have so far not been considered in the development of models that show the likely climate change in the future. The work described here examined the presence and possibility of emission of phthalic acid esters and greenhouse gases from various plastic materials in daily use in the aquatic environment. The article presents, inter alia, research on the influence of temperature (20, 60, and 90 °C), pH (3, 7, and 10), plastic material, time (1, 3, 5, 7, and 14 d), and ultraviolet radiation on the migration of components present in various types of plastics, such as poly(vinyl chloride) (with high and low content of plasticizers) and polypropylene. No significant effect of pH on the migration of the plasticizers from the polymer matrix was observed. In turn, the influence of temperature on the emission of these susceptibilities was determined by the type of polymer. The highest emission level of plasticizers made of poly(vinyl chloride) was recorded for 60 °C, while from polypropylene for 20 °C. Depending on environmental conditions, the degradation of microplastics leads to a reduction in the mass of the material and conversion to methane and carbon dioxide. Each material was degraded, which resulted in the observed migration of components and methane and carbon dioxide emissions from the analysed materials. The highest degree of bis(2-ethylhexyl) phthalate migration was observed for the material made of poly(vinyl chloride). The amount of greenhouse gas emissions depended on the insolation conditions, and the poly(vinyl chloride) material showed the highest emission of methane and carbon dioxide. The highest concentration of methane at the level of 94 ppm after 360 days was observed for poly(vinyl chloride) with a large amount of plasticizers without access to light.

Environmental Impact Assessment of an Organic Wine Production in Central Italy: Case Study from Lazio

Growing awareness of environmental sustainability in the agri-food sector has enhanced the gradual shift toward less-impactful food and organic production systems. In 2021, nearly three million hectolitres of organic wine were produced which accounted for 6% of the whole wine production in Italy (50.2 million hectolitres); thus, registering an increase of almost 60% in the last three years. The economic and cultural importance attributed to Italian wine production worldwide represents a key factor to assess and reduce the environmental burdens associated with the activities of this industry. Furthermore, literature studies have highlighted consumer sensitivity for sustainable winemaking processed, and there is even a trend towards eco-friendly wines. In particular, the bottling stage has been identified as an impactful stage for the environmental performance of the wine life cycle. This study examined the environmental impact assessment of organic wine production in the Lazio region, by performing a “cradle-to-gate” approach according to the life cycle assessment (LCA) methodology. High-quality inventory data for one year of operation was obtained directly from the farming company, “Tenute Filippi” (Cori, Lazio, Italy), and the wine process considered the input from grape cultivation to the winery phases. In these regards, the study also provided an impact assessment for the primary packaging of a 0.75 L wine bottle, with contributions from the different life cycle stages. The results showed a total amount of greenhouse gas emissions (GHGs) of 1.1 kg CO2 eq, that are responsible for climate change. Referring to the individual production input, the primary packaging phase accounted for 55% of the total GHGs, with 0.86 kg CO2 eq per bottle, followed by agricultural fuel use for grape production and harvesting activities, with 0.30 kg CO2 eq. Building on these results, the study provides recommendations on the selection of the most significant and relevant indicators for the environmental life cycle impact assessment, thus, identifying possible hotspots in the wine sector.

Carbon Footprint: The Case of Four Chicken Meat Products Sold on the Spanish Market.

Despite its relatively low environmental impact within the livestock sector, the poultry sector still faces its own environmental challenges that need to be addressed. The present paper uses life cycle assessment to quantify greenhouse gas emissions, from cradle to slaughterhouse gate, of four chicken meat products: whole carcass, wings, breast fillets, and leg quarters. The main contribution of the present study is that it provides a detailed analysis of different chicken meat cuts, testing mass and economic allocation choices and showing that economic allocation better reflects the causality of the cutting process. We recommend that a distinction should be made between whole carcass and meat cuts, as there are significant differences in meat content and climate change results between these two categories. This is not so clear in the literature, nor in the LEAP guideline for the poultry sector. The study was performed by using disaggregated inventory data from Spain, for the first time. Results show that the major contributors to environmental impact are feed production (&gt;70%), electricity use (10.2%), and fossil fuel combustion (8.1%). Packaging did not significantly contribute to the climate change impact of the chicken products evaluated (0.4-3.4% contribution, depending on the type of packaging and product considered).

Atomistic origin of mechanochemical NH3 synthesis on Fe catalysts

A tremendous amount of ammonia (NH3) has been produced by the Haber-Bosch method during the last 100 years. However, it is imperative to develop a new alternative to produce NH3 in a more environmentally friendly way due to the high energy cost and the large amount of greenhouse gas emissions in the Haber-Bosch method. Although the mechanochemical process has been regarded as an emerging technique, the understanding at the atomic level is limited. Here, we computationally model the mechanochemical ball-milling method by molecular dynamics simulations with the reactive force field (ReaxFF) developed in this work. We find that strain applied to Fe surfaces significantly enhances the N2 dissociation as well as the NHx (x = 1–3) formation on Fe(110), whereas the strain effect is negligible on Fe(111). From the von Mises stress analyses, the applied strain (mechanical) energies transfer the Fe catalysts and N atoms adsorbed on Fe surfaces and then activate NHx formation. Moreover, mechanical strain boosts a new mechanism for NH formation, the rate-determining step, via the direct interaction between the dissociated N atom on the Fe surface and the H2 molecule, which is supported by density functional theory calculations. This study shows that the mechanochemical process is readily operated on Fe catalysts and promising for NH3 synthesis.

Impact of Emerging Transport Technologies on Freight Economic and Environmental Performance: A System Dynamics View.

Road freight transport promotes economic development while impeding the future of green development due to excessive fossil fuel use. Road freight enterprises need to adapt to stricter environmental regulations while maintaining a reasonable level of profit. However, this is not easy in a growing economy such as China's, whose domestic freight demand is increasing rapidly with economic growth. The development of emerging transport technologies (ETTs) creates great potential for reducing the negative environmental impact of road freight transport. This study considers five candidate ETTs: eco-driving, fleet platooning, vehicle utilization, optimized vehicle design, and renewable energy trucks. A system dynamics analytical framework is established to explore the long-term impact of ETTs on road profit and greenhouse gas (GHG) emissions under the uncertainty of macroeconomic development. Road freight enterprises affiliated with the Qingdao port in China are taken as a case study. The economic and environmental impact of their adoption of ETTs is projected from 2020 to 2035. The results show that the economic growth in the port hinterland leads to an increase in road freight volume and profit, but it also yields a greater amount of GHG emissions from road transport. All of the candidate ETTs exhibit a positive effect on reducing GHG emissions from road transport, but they also cause profit losses due to a high application cost, even though they reduce transport operating costs by fuel savings. The results of the Sobol sensitivity analysis show that GHG reductions are sensitive to the adoption of ETTs. Thus, a carbon-based compensation mechanism is introduced. With this mechanism, road freight enterprises should prioritize vehicle utilization, optimized vehicle design, and eco-driving in their adoption of ETTs for more sustainable development. The results provide systems-based insights into ETT deployment decisions for road freight companies.

A Playful Approach to Household Sustainability: Results From a Pilot Study on Resource Consumption

Background. U.S. households produce a significant amount of greenhouse gas emissions, indicating a potential to reduce their carbon footprints from changing food, energy, and water (FEW) consumption patterns. Behavioral change to FEW consumption is needed, but difficult to achieve. Interactive and engaging approaches like serious games could be a way to increase awareness of possible measures, leading to more sustainable behavior at a household level. This study looks into the experiences and effects of a digital game for homeowners with the potential to reduce FEW resource consumption impacts. Intervention. In this study, we developed and implemented a digital game to explore its potential to raise awareness of the consumption and conservation of FEW resources and the efficacy of conservation messages. This study aims to measure learning outcomes from game participation and to assess the suitability of the game for informing resource conservation actions. Methods. We tested a proof-of-concept of a digital four-player game, called HomeRUN, with 28 homeowners. The data collected include homeowners’ values and preferences with regard to FEW resources. The patterns of game actions are analyzed with an emphasis on the effectiveness of conservation messaging in informing household consumption behavior. Results. About 65% of the respondents agree that they gained a better understanding of the greenhouse gas emission impacts of FEW resource consumption after playing the game. Over 57% of the respondents agree that the game experience would influence their future consumption behavior, while a quarter of the respondents are unsure. Overall, we demonstrate the HomeRUN game has potential as a tool for informing conservation efforts at a household level.